A trichotomic approach to concept capture and representation: With its application to library data mining

Toshiro Minami, Sachio Hirokawa, Kensuke Baba, Eriko Amano

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The aim of this chapter is twofold. Firstly, we propose a method of specifying the concept that is too hard to describe in an exact way by a word or a phrase, by setting up the “relative distances" from three key concepts; which we call a trichotomic approach to concept capture and representation, or description, in an approximate means. It is important and interesting that we can choose not only the key words but also other three “keys" such as patrons, books, concepts, objects or others. Then we arrange the objects of study according to the relative distances from these three keys, and investigate how these objects are distributed. Secondly, we demonstrate the usefulness of trichotomic approach through a couple of case studies applied to library’s loan record analysis. In these case studies, we discuss and compare the methods of choosing three keys, then we show how the trichotomic representation method is applied to the real data analysis. From these case studies, we are convinced of its high potential and importance as a visualization tool of the results of data analysis in general.

    Original languageEnglish
    Pages (from-to)61-75
    Number of pages15
    JournalStudies in Computational Intelligence
    Volume553
    DOIs
    Publication statusPublished - 2014

    All Science Journal Classification (ASJC) codes

    • Artificial Intelligence

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